The Impact of the COVID-19 Pandemic on the Uptake of Influenza Vaccine: UK-Wide Observational Study
Notice bibliographique
Résumé
ABSTRACT Objectives The objective of this study was to measure the impact of the Covid-19 pandemic on acceptance of flu vaccination in the 2020-21 season, including for those newly eligible for the UK National Health Service (NHS) free vaccination programme, extended this year to include an estimated 32.4 million (48.8%) of the UK population. Knowing intended uptake is essential to inform supply and steer public health messaging to maximise vaccination given the combined threats of both flu and Covid-19 — the unknown impact of which on both attitudes and the need for mass uptake yet again create the threat of ill-informed planning resulting in failure to meet necessary public health demand. Methods An online questionnaire posing question items on influenza vaccination was administered to registrants of the Care Information Exchange (CIE), the NHS’s largest patient electronic personal health record. This was part of a longitudinal study initiated during the Covid-19 pandemic lockdown. This analysis was limited to those who, in line with established NHS criteria, were previously or newly eligible but had not routinely received seasonal influenza vaccination in the past. Groups were stratified by response (yes/no) to intending to receive flu vaccination in 2020-21: Group 1.) Previously eligible now responding ‘yes’, 2.) Previously eligible still responding ‘no’, 3.) Newly eligible responding ‘yes’, and 4.) Newly eligible responding ‘no’. Within these groups, response by health worker status and each group’s inclination to vaccinate school age children was also measured. Summary statistics were reported alongside univariate and multivariable regression. Lastly, a network analysis visualised the frequency and co-occurrence of reasons qualifying response for or against influenza vaccination in 2020/21. Findings Among 6,641 respondents, 4,040 (61.1%) had previously routinely received the flu vaccination. 1,624 (24.5%) had been either previously eligible but not vaccinated (945, 58.2%) or newly eligible (679, 41.8%). Among the previously eligible participants who had not routinely received influenza vaccination 536 (56.7%) responded they would in 2020-21, increasing the vaccination rate in the entire previously eligible cohort from 79.6% to 91.2%, and 466 (68.6%) in the newly eligible. Multivariable logistic regression resulted in few substantial changes to effect estimates, with the exception of age, for which all estimates showed a stronger association with intention to receive the flu vaccine. In those who became newly eligible to receive the flu vaccine, there was an association between intention to receive the flu vaccine and increased age (OR = 1.07, 95% CI 1.03 to 1.12), IMD quintile, and considering oneself at high risk from Covid-19 (OR = 1.80, 95% CI 1.22 to 2.70). Network analysis showed the most frequent themes for previously eligible unvaccinated and newly eligible participants accepting vaccination in 2020/21 were: ‘precaution for myself’ (41.2% and 46.1%) and ‘Covid-19’ (27.4% and 27.1%), where the former was qualified by the latter in 36% and 29.1% of responses. Among the previously and newly eligible not intending to receive vaccination in 2020/21, misinformed themes of ‘makes me unwell’, ‘gives me flu’ and ‘vaccine doesn’t work’ were present across 37.4% and 21.9% of responses, respectively. Among participants with school age children, of those previously eligible who now intend to be vaccinated themselves, 82.5% also intend to vaccinate their children in 2020/21 compared to 25.8% of those who would not accept the influenza vaccine for themselves. Among the newly eligible respondents this was 82.1% and 43.5%, respectively. 49.9% of the previously unvaccinated healthcare workers would continue to decline the vaccine in 2020/21. Interpretation In this UK-wide observational study, Covid-19 has increased acceptance of flu vaccination in 2020/21 from 79.6% to 91.2% in those previously eligible, and for the 69% of those newly eligible. This high anticipated vaccination rate (to 26 million (80%) of the UK population) requires appropriate planning, but can be further increased with effective messaging campaigns to address negative misconceptions about flu vaccination, which may also help in preparation for future Covid-19 vaccination. It remains of concern that 50% of healthcare professionals who refused it previously still do not intend to have the flu vaccine.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,002 | 0,008 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,001 | 0,002 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,002 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,004 | 0,001 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».